On the limitations of comparing mean square forecast errors

Linear models are invariant under non-singular, scale-preserving linear transformations, whereas mean square forecast errors (MSFEs) are not. Different rankings may result across models or methods from choosing alternative yet isomorphic representations of a process. One approach can dominate others for comparisons in levels, yet lose to another for differences, to a second for cointegrating vectors and to a third for combinations of variables. The potential for switches in ranking is related to criticisms of the inadequacy of MSFE against encompassing criteria, which are invariant under linear transforms and entail MSFE dominance. An invariant evaluation criterion which avoids misleading outcomes is examined in a Monte Carlo study of forecasting methods.     

Influence of hydrochlorothiazide on the pain threshold and on the antinociceptive activity of morphine,in rats

Summary Hydrochlorothiazide, acutely injected in rats, has a weak analgesic activity per se and potentiates and prolongs the antinociceptive effect of morphine.This work was supported in part by grants from Consiglio Nazionale delle Ricerche, and by Ministero della Pubblica Istruzione, Roma.     

Forecast accuracy after pretesting with an application to the stock market

In econometrics, as a rule, the same data set is used to select the model and, conditional on the selected model, to forecast. However, one typically reports the properties of the (conditional) forecast, ignoring the fact that its properties are affected by the model selection (pretesting). This is wrong, and in this paper we show that the error can be substantial. We obtain explicit expressions for this error. To illustrate the theory we consider a regression approach to stock market forecasting, and show that the standard predictions ignoring pretesting are much less robust than naive econometrics might suggest. We also propose a forecast procedure based on the ‘neutral Laplace estimator’, which leads to an improvement over standard model selection procedures. Copyright © 2004 John Wiley & Sons, Ltd.     

Preferential excretion of glycated albumin in C57BL-Ks-J mice: effects of diabetes.

Urinary excretion of glycated albumin was quantitated in genetically hyperglycemic mice (C57BL-Ks-J, db/db mice), a model for non-insulin-dependent diabetes mellitus, and compared with their non-diabetic littermates. The data indicated a preferential excretion of glycated albumin in non-diabetic mice. This phenomenon of 'editing' of glycated albumin is decreased significantly in diabetic mice. Quantitative measurements of overall excretion of glycated albumin suggested that the loss of editing in diabetic mice is due to the dilution of glycated albumin by the unmodified albumin which is excreted in large amounts in diabetic mice. Therefore, the loss of editing observed in this model resembled the one we characterized in insulin-dependent diabetic humans and a streptozotocin-diabetic rat model.     

Exponential smoothing: Behavior of the ex-post sum of squares near 0 and 1

When using simple exponential smoothing on a given time series the nature of the relationship between the optimal smoothing constant and the autocorrelation structure of the series remains an unresolved question. Although numerical search routines can easily be used to find optimal values of the smoothing constant, they offer little insight into the nature of the relationship between the estimated smoothing constant and the structure of the underlying time series. We suggest that renewed investigations of the ex-post sum of squares function may prove helpful in this pursuit. Results are presented that illustrate how the optimal smoothing constant depends upon the value used to initialize the smoothing and upon the sample autocorrelation coefficients of the observed series. These results are based on a new formula for the derivative of the ex-post sum of squares function. In particular, the derivative is examined near 0 and 1, where great simplifications occur in its form, thereby facilitating investigations near these points. A necessary and sufficient condition is stated for when the ex-post sum of squares must have a positive derivative at 0 and the autocorrelation coefficients of the differenced series are shown to affect the sign of the derivative near 1. Based on these results, a general algorithm is presented as an alternative to grid search routines for minimizing the ex-post sum of squares.     

Growth hormone signal transduction

Growth hormone (GH) promotes animal growth by stimulating bone and cartilage cell proliferation, and influences carbohydrate and lipid metabolism. Some of these effects are brought about indirectly via somatomedin induction in hepatocytes, others by acting directly on the target cells. In either case, GH first binds to specific receptors on cells to trigger a sequence of biochemical events culminating in a biological response. Recently much has been learnt about the molecular structure of GH receptor, its binding to ligand, and the ensuing signal transduction events.